"While automation and AI solutions differ technically in many ways, the core distinction comes down to determinism versus probability. Deterministic systems behave the same every time A deterministic system produces the same output every time for a given input: Input → fixed logic → output No interpretation No ambiguity If two people run the same input through the system, they get the same result"
"Since then, a lot has changed in the field. From generative AI to agentic AI, new technologies have helped technologists to build AI-powered products for a wide range of businesses. This rapid progress has put product managers in an interesting position, as many teams are now being asked to build AI solutions. But does every product actually require an AI solution? I don't think so."
AI adoption accelerated after public release of conversational LLMs, driving rapid advances from generative to agentic AI and widespread product development. Product teams face choices between deterministic automation and probabilistic AI when solving problems. Deterministic systems use fixed logic to produce identical outputs for the same input, offering no ambiguity and predictable behavior. Probabilistic systems use inference to generate best-guess outputs, allowing multiple reasonable answers and sensitivity to small input changes. Not every product requires AI; manual automation can suffice for clear rules. A practical decision framework can guide whether to apply automation, AI, or a hybrid approach based on task determinism and ambiguity.
Read at LogRocket Blog
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